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Founder who built Snap's AI launches a snappy new take on video chatbots | TechCrunch

Dec 11, 2024 - techcrunch.com
eSelf, a startup co-founded by Dr. Alan Bekker and Eylon Shoshan, has emerged from stealth with $4.5 million in seed funding to develop real-time, video-based conversational AI agents. The platform aims to create more interactive and lifelike AI assistants, initially targeting sectors like education, sales, financial services, real estate, and health and wellness. eSelf's agents boast a response time of under 1.7 seconds, faster than many competitors, and can operate common apps to perform tasks similar to a human assistant. The startup has launched a no-code creation studio for customers to build their own agents and has already facilitated millions of real-time conversations with clients like Christie's real estate and Brazilian bank AGI.

Bekker, who previously founded Voca and sold it to Snap for $100 million, has a background in voice recognition, neural networks, and deep learning. After leaving Snap, he envisioned a new generation of AI agents using video and voice for more humanlike interactions. eSelf leverages fine-tuned models like Meta's Llama rather than building its own large language models from scratch, offering an alternative to existing chatbot solutions with potentially lower latency. The startup is part of a growing field of companies exploring the "agentic" opportunity, aiming to deliver more believable AI responses through advanced generative AI technologies.

Key takeaways:

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  • eSelf, a startup co-founded by Dr. Alan Bekker and Eylon Shoshan, has emerged from stealth with $4.5 million in seed funding to develop real-time, video-based conversational AI agents.
  • The platform focuses on verticals such as education, sales, financial services, real estate, and health and wellness, offering a "no-code" creation studio for building AI agents.
  • eSelf's agents boast a response time of under 1.7 seconds, claiming to be faster and more lifelike than competitors like OpenAI.
  • The startup leverages fine-tuned Meta-created Llama models instead of building its own LLMs, allowing customers to switch from existing chatbots with potentially longer latency.
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